Data Optimization

Data Optimization controls which data-platform optimizations can run automatically, require approval, or remain manual.

Open Data Optimization

Go to Automation > Data Optimization.

Configure governance

1. Confirm that a Data Platform source is connected.
2. Review the available optimization categories and their current mode.
3. Choose manual, approval-required, or automatic operation only where the UI permits it.
4. Review scope, risk, and ownership.
5. Save the control changes.
6. Monitor resulting approvals and outcomes in the related workflow and Data Platform pages.

Best practices

• Begin with manual or approval-required settings.
• Separate production and non-production scopes.
• Require an owner and rollback plan for data-compute changes.
• Review query, pipeline, warehouse, and table recommendations in context.
• Confirm that data freshness and coverage are sufficient before automation.

Example rollout

Phase	Recommended setting	Exit criteria
Observe	Manual review	Data Platform owners agree the recommendations match real workloads.
Govern	Approval required	Owners, rollback steps, and change windows are documented.
Automate	Automatic for selected low-risk scopes	The same action has passed review repeatedly without incident.

Use separate controls for production and non-production where available. Production data warehouses, pipelines, and tables should keep approval gates unless your organization has a tested rollback process.